Understanding Worker's Approach in a Conventional Assembly Line: An Observational Case Study Using Content and Network Analysis

Snehal Dhengre, Ling Rothrock

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Consistency in workers' performance is critical to making a system reliable and efficient. Standardizing the work process, often documented as a standard operating procedure, helps maintain consistency. However, standardizing assembly procedures and ensuring consistent performance in conventional assembly lines where workers play a significant role is challenging. This paper presents a methodology to analyze workers' performance in the manufacturing system by examining their work and behavior to create effective standard procedures. First, task analysis was carried out to identify the expected way of performing the assembly task per standard operating procedure. Next, the workers were monitored performing the assembly to conduct content analysis. Lastly, a network analysis was done to study the sequence of tasks followed by the worker. The findings suggest that the workers perceived and executed the assembly differently with some deviations from the standard operating procedure, indicating variability in performance. Furthermore, clusters of tasks frequently carried out during the assembly varied among the observed workers. This methodology can assist manufacturing industries in creating effective standard operating procedures by providing insight into workers' performance. In particular, how workers accomplished the task, the process followed, errors committed, and difficulties encountered during the task. It is also proposed that the methodology will improve plan formation, such as modification of the workstation and assembly process to increase overall system performance.

Original languageEnglish (US)
Title of host publicationProceedings of the 2022 IEEE International Conference on Human-Machine Systems, ICHMS 2022
EditorsDavid Kaber, Antonio Guerrieri, Giancarlo Fortino, Andreas Nurnberger
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665452380
DOIs
StatePublished - 2022
Event3rd IEEE International Conference on Human-Machine Systems, ICHMS 2022 - Orlando, United States
Duration: Nov 17 2022Nov 19 2022

Publication series

NameProceedings of the 2022 IEEE International Conference on Human-Machine Systems, ICHMS 2022

Conference

Conference3rd IEEE International Conference on Human-Machine Systems, ICHMS 2022
Country/TerritoryUnited States
CityOrlando
Period11/17/2211/19/22

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Media Technology
  • Control and Optimization

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